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                                            <h1><a href="https://www.cnblogs.com/vipchenwei/p/7239953.html" rel="nofollow" id="cb_post_title_url">深度理解python中的元类</a></h1>

<p>记录学习   不过写的还是非常好的，仔细看！</p>

<p>本文转自:（英文版）https://stackoverflow.com/questions/100003/what-is-a-metaclass-in-python</p>

<p>　　　　  (翻译版)   http://python.jobbole.com/21351/</p>

<p>以下代码测试环境为ptyon2.7</p>

<p><strong>类也是对象</strong></p>

<p><strong>　　在理解元类之前，你需要先掌握Python中的类。Python中类的概念借鉴于Smalltalk，这显得有些奇特。在大多数编程语言中，类就是一组用来描述如何生成一个对象的代码段。在Python中这一点仍然成立：</strong></p>

<p><a><img alt="复制代码" class="has" src="https://common.cnblogs.com/images/copycode.gif" /></a></p>

<pre>
&gt;&gt;&gt; class ObjectCreator(object):
...       pass
... 

&gt;&gt;&gt; my_object = ObjectCreator()
&gt;&gt;&gt; print(my_object)
&lt;__main__.ObjectCreator object at 0x8974f2c&gt;</pre>

<p><a><img alt="复制代码" class="has" src="https://common.cnblogs.com/images/copycode.gif" /></a></p>

<p>　　但是，Python中的类还远不止如此。类同样也是一种对象。是的，没错，就是对象。只要你使用关键字class，Python解释器在执行的时候就会创建一个对象。下面的代码段：</p>

<pre>
&gt;&gt;&gt; class ObjectCreator(object):
...       pass
... </pre>

<p>　　将在内存中创建一个对象，名字就是ObjectCreator。<strong>这个对象（类）自身拥有创建对象（类实例）的能力，而这就是为什么它是一个类的原因。</strong>但是，它的本质仍然是一个对象，于是乎你可以对它做如下的操作：</p>

<p>　　1)   你可以将它赋值给一个变量</p>

<p>　　2)   你可以拷贝它</p>

<p>　　3)   你可以为它增加属性</p>

<p>　　4)   你可以将它作为函数参数进行传递</p>

<p>　　下面是示例：</p>

<p><a><img alt="复制代码" class="has" src="https://common.cnblogs.com/images/copycode.gif" /></a></p>

<pre>
&gt;&gt;&gt; print ObjectCreator     # 你可以打印一个类，因为它其实也是一个对象
&lt;class '__main__.ObjectCreator'&gt;
&gt;&gt;&gt; def echo(o):
…       print o
…
&gt;&gt;&gt; echo(ObjectCreator)                 # 你可以将类做为参数传给函数
&lt;class '__main__.ObjectCreator'&gt;
&gt;&gt;&gt; print hasattr(ObjectCreator, 'new_attribute')
Fasle
&gt;&gt;&gt; ObjectCreator.new_attribute = 'foo' #  你可以为类增加属性
&gt;&gt;&gt; print hasattr(ObjectCreator, 'new_attribute')
True
&gt;&gt;&gt; print ObjectCreator.new_attribute
foo
&gt;&gt;&gt; ObjectCreatorMirror = ObjectCreator # 你可以将类赋值给一个变量
&gt;&gt;&gt; print ObjectCreatorMirror()
&lt;__main__.ObjectCreator object at 0x8997b4c&gt;</pre>

<p><a><img alt="复制代码" class="has" src="https://common.cnblogs.com/images/copycode.gif" /></a></p>

<p><strong>　　动态地创建类</strong></p>

<p>因为类也是对象，你可以在运行时动态的创建它们，就像其他任何对象一样。首先，你可以在函数中创建类，使用class关键字即可。</p>

<p><a><img alt="复制代码" class="has" src="https://common.cnblogs.com/images/copycode.gif" /></a></p>

<pre>
&gt;&gt;&gt; def choose_class(name):
…       if name == 'foo':
…           class Foo(object):
…               pass
…           return Foo     # 返回的是类，不是类的实例
…       else:
…           class Bar(object):
…               pass
…           return Bar
…
&gt;&gt;&gt; MyClass = choose_class('foo')
&gt;&gt;&gt; print MyClass              # 函数返回的是类，不是类的实例
&lt;class '__main__'.Foo&gt;
&gt;&gt;&gt; print MyClass()            # 你可以通过这个类创建类实例，也就是对象
&lt;__main__.Foo object at 0x89c6d4c&gt;</pre>

<p><a><img alt="复制代码" class="has" src="https://common.cnblogs.com/images/copycode.gif" /></a></p>

<p>　　但这还不够动态，因为你仍然需要自己编写整个类的代码。由于类也是对象，所以它们必须是通过什么东西来生成的才对。当你使用class关键字时，Python解释器自动创建这个对象。但就和Python中的大多数事情一样，Python仍然提供给你手动处理的方法。还记得内建函数type吗？这个古老但强大的函数能够让你知道一个对象的类型是什么，就像这样：</p>

<p><a><img alt="复制代码" class="has" src="https://common.cnblogs.com/images/copycode.gif" /></a></p>

<pre>
&gt;&gt;&gt; print type(1)
&lt;type 'int'&gt;
&gt;&gt;&gt; print type("1")
&lt;type 'str'&gt;
&gt;&gt;&gt; print type(ObjectCreator)
&lt;type 'type'&gt;
&gt;&gt;&gt; print type(ObjectCreator())
&lt;class '__main__.ObjectCreator'&gt;</pre>

<p><a><img alt="复制代码" class="has" src="https://common.cnblogs.com/images/copycode.gif" /></a></p>

<p>　　这里，type有一种完全不同的能力，它也能动态的创建类。type可以接受一个类的描述作为参数，然后返回一个类。（我知道，根据传入参数的不同，同一个函数拥有两种完全不同的用法是一件很傻的事情，但这在Python中是为了保持向后兼容性）</p>

<p>type可以像这样工作：</p>

<pre>
type(类名, 父类的元组（针对继承的情况，可以为空），包含属性的字典（名称和值）)</pre>

<p>　　比如下面的代码：</p>

<pre>
&gt;&gt;&gt; class MyShinyClass(object):
…       pass</pre>

<p>　　可以手动像这样创建：</p>

<pre>
&gt;&gt;&gt; MyShinyClass = type('MyShinyClass', (), {})  # 返回一个类对象
&gt;&gt;&gt; print MyShinyClass
&lt;class '__main__.MyShinyClass'&gt;
&gt;&gt;&gt; print MyShinyClass()  #  创建一个该类的实例
&lt;__main__.MyShinyClass object at 0x8997cec&gt;　</pre>

<p>　　你会发现我们使用“MyShinyClass”作为类名，并且也可以把它当做一个变量来作为类的引用。类和变量是不同的，这里没有任何理由把事情弄的复杂。</p>

<p>　　type 接受一个字典来为类定义属性，因此:</p>

<pre>
&gt;&gt;&gt; class Foo(object):
…       bar = True</pre>

<p>　　可以翻译为：</p>

<pre>
&gt;&gt;&gt; Foo = type('Foo', (), {'bar':True})</pre>

<p>　　并且可以将Foo当成一个普通的类一样使用：</p>

<p><a><img alt="复制代码" class="has" src="https://common.cnblogs.com/images/copycode.gif" /></a></p>

<pre>
&gt;&gt;&gt; print Foo
&lt;class '__main__.Foo'&gt;
&gt;&gt;&gt; print Foo.bar
True
&gt;&gt;&gt; f = Foo()
&gt;&gt;&gt; print f
&lt;__main__.Foo object at 0x8a9b84c&gt;
&gt;&gt;&gt; print f.bar
True</pre>

<p><a><img alt="复制代码" class="has" src="https://common.cnblogs.com/images/copycode.gif" /></a></p>

<p>　　当然，你可以向这个类继承，所以，如下的代码：</p>

<pre>
&gt;&gt;&gt; class FooChild(Foo):
…       pass</pre>

<p>　　就可以写成：</p>

<pre>
&gt;&gt;&gt; FooChild = type('FooChild', (Foo,),{})
&gt;&gt;&gt; print FooChild
&lt;class '__main__.FooChild'&gt;
&gt;&gt;&gt; print FooChild.bar   # bar属性是由Foo继承而来
True</pre>

<p>　　最终你会希望为你的类增加方法。只需要定义一个有着恰当签名的函数并将其作为属性赋值就可以了。</p>

<p><a><img alt="复制代码" class="has" src="https://common.cnblogs.com/images/copycode.gif" /></a></p>

<pre>
&gt;&gt;&gt; def echo_bar(self):
…       print self.bar
…
&gt;&gt;&gt; FooChild = type('FooChild', (Foo,), {'echo_bar': echo_bar})
&gt;&gt;&gt; hasattr(Foo, 'echo_bar')
False
&gt;&gt;&gt; hasattr(FooChild, 'echo_bar')
True
&gt;&gt;&gt; my_foo = FooChild()
&gt;&gt;&gt; my_foo.echo_bar()
True</pre>

<p><a><img alt="复制代码" class="has" src="https://common.cnblogs.com/images/copycode.gif" /></a></p>

<p>　　你可以看到，在Python中，类也是对象，你可以动态的创建类。这就是当你使用关键字class时Python在幕后做的事情，而这就是通过元类来实现的。</p>

<p><strong>　　到底什么是元类（终于到主题了）</strong></p>

<p>元类就是用来创建类的“东西”。你创建类就是为了创建类的实例对象，不是吗？但是我们已经学习到了Python中的类也是对象。好吧，元类就是用来创建这些类（对象）的，元类就是类的类，你可以这样理解 为：</p>

<pre>
MyClass = MetaClass()
MyObject = MyClass()</pre>

<p>　　你已经看到了type可以让你像这样做：</p>

<pre>
MyClass = type('MyClass', (), {})</pre>

<p>　　这是因为函数type实际上是一个元类。type就是Python在背后用来创建所有类的元类。现在你想知道那为什么type会全部采用小写形式而不是Type呢？好吧，我猜这是为了和str保持一致性，str是用来创建字符串对象的类，而int是用来创建整数对象的类。type就是创建类对象的类。你可以通过检查__class__属性来看到这一点。Python中所有的东西，注意，我是指所有的东西——都是对象。这包括整数、字符串、函数以及类。它们全部都是对象，而且它们都是从一个类创建而来。</p>

<p><a><img alt="复制代码" class="has" src="https://common.cnblogs.com/images/copycode.gif" /></a></p>

<pre>
&gt;&gt;&gt; age = 35
&gt;&gt;&gt; age.__class__
&lt;type 'int'&gt;
&gt;&gt;&gt; name = 'bob'
&gt;&gt;&gt; name.__class__
&lt;type 'str'&gt;
&gt;&gt;&gt; def foo(): pass
&gt;&gt;&gt;foo.__class__
&lt;type 'function'&gt;
&gt;&gt;&gt; class Bar(object): pass
&gt;&gt;&gt; b = Bar()
&gt;&gt;&gt; b.__class__
&lt;class '__main__.Bar'&gt;</pre>

<p><a><img alt="复制代码" class="has" src="https://common.cnblogs.com/images/copycode.gif" /></a></p>

<p>　　现在，对于任何一个__class__的__class__属性又是什么呢？</p>

<p><a><img alt="复制代码" class="has" src="https://common.cnblogs.com/images/copycode.gif" /></a></p>

<pre>
&gt;&gt;&gt; a.__class__.__class__
&lt;type 'type'&gt;
&gt;&gt;&gt; age.__class__.__class__
&lt;type 'type'&gt;
&gt;&gt;&gt; foo.__class__.__class__
&lt;type 'type'&gt;
&gt;&gt;&gt; b.__class__.__class__
&lt;type 'type'&gt;</pre>

<p><a><img alt="复制代码" class="has" src="https://common.cnblogs.com/images/copycode.gif" /></a></p>

<p>　　因此，元类就是创建类这种对象的东西。如果你喜欢的话，可以把元类称为“类工厂”（不要和工厂类搞混了:D） type就是Python的内建元类，当然了，你也可以创建自己的元类。</p>

<p><strong>　　__metaclass__</strong><strong>属性</strong></p>

<p>你可以在写一个类的时候为其添加__metaclass__属性。</p>

<pre>
class Foo(object):
    __metaclass__ = something…
[…]</pre>

<p>　　如果你这么做了，Python就会用元类来创建类Foo。小心点，这里面有些技巧。你首先写下class Foo(object)，但是类对象Foo还没有在内存中创建。Python会在类的定义中寻找__metaclass__属性，如果找到了，Python就会用它来创建类Foo，如果没有找到，就会用内建的type来创建这个类。把下面这段话反复读几次。当你写如下代码时 :</p>

<pre>
class Foo(Bar):
    pass</pre>

<p>　　</p>

<p>　　Python做了如下的操作：</p>

<p>　　Foo中有__metaclass__这个属性吗？如果是，Python会在内存中通过__metaclass__创建一个名字为Foo的类对象（我说的是类对象，请紧跟我的思路）。如果Python没有找到__metaclass__，它会继续在Bar（父类）中寻找__metaclass__属性，并尝试做和前面同样的操作。如果Python在任何父类中都找不到__metaclass__，它就会在模块层次中去寻找__metaclass__，并尝试做同样的操作。如果还是找不到__metaclass__,Python就会用内置的type来创建这个类对象。</p>

<p>现在的问题就是，你可以在__metaclass__中放置些什么代码呢？答案就是：可以创建一个类的东西。那么什么可以用来创建一个类呢？type，或者任何使用到type或者子类化type的东东都可以。</p>

<p> </p>

<p><strong>自定义元类</strong></p>

<p>　　元类的主要目的就是为了当创建类时能够自动地改变类。通常，你会为API做这样的事情，你希望可以创建符合当前上下文的类。假想一个很傻的例子，你决定在你的模块里所有的类的属性都应该是大写形式。有好几种方法可以办到，但其中一种就是通过在模块级别设定__metaclass__。采用这种方法，这个模块中的所有类都会通过这个元类来创建，我们只需要告诉元类把所有的属性都改成大写形式就万事大吉了。</p>

<p>　　幸运的是，__metaclass__实际上可以被任意调用，它并不需要是一个正式的类（我知道，某些名字里带有‘class’的东西并不需要是一个class，画画图理解下，这很有帮助）。所以，我们这里就先以一个简单的函数作为例子开始。</p>

<p><a><img alt="复制代码" class="has" src="https://common.cnblogs.com/images/copycode.gif" /></a></p>

<pre>
# 元类会自动将你通常传给‘type’的参数作为自己的参数传入
def upper_attr(future_class_name, future_class_parents, future_class_attr):
    '''返回一个类对象，将属性都转为大写形式'''
    #  选择所有不以'__'开头的属性
    attrs = ((name, value) for name, value in future_class_attr.items() if not name.startswith('__'))
     # 将它们转为大写形式
    uppercase_attr = dict((name.upper(), value) for name, value in attrs)
 
    # 通过'type'来做类对象的创建
    return type(future_class_name, future_class_parents, uppercase_attr)
 
__metaclass__ = upper_attr  #  这会作用到这个模块中的所有类
 
class Foo(object):
    # 我们也可以只在这里定义__metaclass__，这样就只会作用于这个类中
    bar = 'bip'

print hasattr(Foo, 'bar')
# 输出: False
print hasattr(Foo, 'BAR')
# 输出:True
 
f = Foo()
print f.BAR
# 输出:'bip'</pre>

<p><a><img alt="复制代码" class="has" src="https://common.cnblogs.com/images/copycode.gif" /></a></p>

<p><img alt="" class="has" id="code_img_closed_88f41fde-c611-406b-a23f-ddfcd72482d6" src="https://images.cnblogs.com/OutliningIndicators/ContractedBlock.gif" /> Python3.x实现上述方式</p>

<p> </p>

<p>　　现在让我们再做一次，这一次用一个真正的class来当做元类。</p>

<p><a><img alt="复制代码" class="has" src="https://common.cnblogs.com/images/copycode.gif" /></a></p>

<pre>
# 请记住，'type'实际上是一个类，就像'str'和'int'一样
# 所以，你可以从type继承
class UpperAttrMetaClass(type):
    # __new__ 是在__init__之前被调用的特殊方法
    # __new__是用来创建对象并返回之的方法
    # 而__init__只是用来将传入的参数初始化给对象
    # 你很少用到__new__，除非你希望能够控制对象的创建
    # 这里，创建的对象是类，我们希望能够自定义它，所以我们这里改写__new__
    # 如果你希望的话，你也可以在__init__中做些事情
    # 还有一些高级的用法会涉及到改写__call__特殊方法，但是我们这里不用
    def __new__(upperattr_metaclass, future_class_name, future_class_parents, future_class_attr):
        attrs = ((name, value) for name, value in future_class_attr.items() if not name.startswith('__'))
        uppercase_attr = dict((name.upper(), value) for name, value in attrs)
        return type(future_class_name, future_class_parents, uppercase_attr)</pre>

<p><a><img alt="复制代码" class="has" src="https://common.cnblogs.com/images/copycode.gif" /></a></p>

<p>　　但是，这种方式其实不是OOP。我们直接调用了type，而且我们没有改写父类的__new__方法。现在让我们这样去处理:</p>

<p><a><img alt="复制代码" class="has" src="https://common.cnblogs.com/images/copycode.gif" /></a></p>

<pre>
class UpperAttrMetaclass(type):
    def __new__(upperattr_metaclass, future_class_name, future_class_parents, future_class_attr):
        attrs = ((name, value) for name, value in future_class_attr.items() if not name.startswith('__'))
        uppercase_attr = dict((name.upper(), value) for name, value in attrs)
 
        # 复用type.__new__方法
        # 这就是基本的OOP编程，没什么魔法
        return type.__new__(upperattr_metaclass, future_class_name, future_class_parents, uppercase_attr)</pre>

<p><a><img alt="复制代码" class="has" src="https://common.cnblogs.com/images/copycode.gif" /></a></p>

<p>　　你可能已经注意到了有个额外的参数upperattr_metaclass，这并没有什么特别的。类方法的第一个参数总是表示当前的实例，就像在普通的类方法中的self参数一样。当然了，为了清晰起见，这里的名字我起的比较长。但是就像self一样，所有的参数都有它们的传统名称。因此，在真实的产品代码中一个元类应该是像这样的：</p>

<pre>
class UpperAttrMetaclass(type):
    def __new__(cls, name, bases, dct):
        attrs = ((name, value) for name, value in dct.items() if not name.startswith('__')
        uppercase_attr  = dict((name.upper(), value) for name, value in attrs)
        return type.__new__(cls, name, bases, uppercase_attr)</pre>

<p>　　如果使用super方法的话，我们还可以使它变得更清晰一些，这会缓解继承（是的，你可以拥有元类，从元类继承，从type继承）</p>

<pre>
class UpperAttrMetaclass(type):
    def __new__(cls, name, bases, dct):
        attrs = ((name, value) for name, value in dct.items() if not name.startswith('__'))
        uppercase_attr = dict((name.upper(), value) for name, value in attrs)
        return super(UpperAttrMetaclass, cls).__new__(cls, name, bases, uppercase_attr)</pre>

<p>　　就是这样，除此之外，关于元类真的没有别的可说的了。使用到元类的代码比较复杂，这背后的原因倒并不是因为元类本身，而是因为你通常会使用元类去做一些晦涩的事情，依赖于自省，控制继承等等。确实，用元类来搞些“黑暗魔法”是特别有用的，因而会搞出些复杂的东西来。但就元类本身而言，它们其实是很简单的：</p>

<p>　　1)   拦截类的创建</p>

<p>　　2)   修改类</p>

<p>　　3)   返回修改之后的类</p>

<p> </p>

<p><strong>为什么要用metaclass类而不是函数?</strong></p>

<p>　　由于__metaclass__可以接受任何可调用的对象，那为何还要使用类呢，因为很显然使用类会更加复杂啊？这里有好几个原因：</p>

<p>　　1）  意图会更加清晰。当你读到UpperAttrMetaclass(type)时，你知道接下来要发生什么。</p>

<p>　　2） 你可以使用OOP编程。元类可以从元类中继承而来，改写父类的方法。元类甚至还可以使用元类。</p>

<p>　　3）  你可以把代码组织的更好。当你使用元类的时候肯定不会是像我上面举的这种简单场景，通常都是针对比较复杂的问题。将多个方法归总到一个类中会很有帮助，也会使得代码更容易阅读。</p>

<p>　　4） 你可以使用__new__, __init__以及__call__这样的特殊方法。它们能帮你处理不同的任务。就算通常你可以把所有的东西都在__new__里处理掉，有些人还是觉得用__init__更舒服些。</p>

<p>　　5） 哇哦，这东西的名字是metaclass，肯定非善类，我要小心！</p>

<p> </p>

<p><strong>究竟为什么要使用元类？</strong></p>

<p>　　现在回到我们的大主题上来，究竟是为什么你会去使用这样一种容易出错且晦涩的特性？好吧，一般来说，你根本就用不上它：</p>

<p><em>　　“元类就是深度的魔法，99%的用户应该根本不必为此操心。如果你想搞清楚究竟是否需要用到元类，那么你就不需要它。那些实际用到元类的人都非常清楚地知道他们需要做什么，而且根本不需要解释为什么要用元类。”  —— Python界的领袖 Tim Peters</em></p>

<p>　　元类的主要用途是创建API。一个典型的例子是Django ORM。它允许你像这样定义：</p>

<pre>
class Person(models.Model):
    name = models.CharField(max_length=30)
    age = models.IntegerField()</pre>

<p>　　但是如果你像这样做的话：</p>

<pre>
guy  = Person(name='bob', age='35')
print guy.age</pre>

<p>　　这并不会返回一个IntegerField对象，而是会返回一个int，甚至可以直接从数据库中取出数据。这是有可能的，因为models.Model定义了__metaclass__， 并且使用了一些魔法能够将你刚刚定义的简单的Person类转变成对数据库的一个复杂hook。Django框架将这些看起来很复杂的东西通过暴露出一个简单的使用元类的API将其化简，通过这个API重新创建代码，在背后完成真正的工作。</p>

<p> </p>

<p><strong>结语</strong></p>

<p>　　首先，你知道了类其实是能够创建出类实例的对象。好吧，事实上，类本身也是实例，当然，它们是元类的实例。</p>

<pre>
&gt;&gt;&gt;class Foo(object): pass
&gt;&gt;&gt; id(Foo)
142630324</pre>

<p>　　Python中的一切都是对象，它们要么是类的实例，要么是元类的实例，除了type。type实际上是它自己的元类，在纯Python环境中这可不是你能够做到的，这是通过在实现层面耍一些小手段做到的。其次，元类是很复杂的。对于非常简单的类，你可能不希望通过使用元类来对类做修改。你可以通过其他两种技术来修改类：</p>

<p>　　1） <a href="http://en.wikipedia.org/wiki/Monkey_patch" rel="nofollow">Monkey patching</a></p>

<p>　　2)   class decorators</p>

<p>　　当你需要动态修改类时，99%的时间里你最好使用上面这两种技术。当然了，其实在99%的时间里你根本就不需要动态修改类 :D</p>
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